Introduction

Abstract

In recent years, various natural disasters have been occurring frequently and showing an increasing trend. Disasters such as typhoons, heavy rainfall, geological earthquakes, snow and ice storms, and others have caused significant losses to the power grid, severely impacting the safe and stable operation of the grid and the normal production and operation of companies.

1.1 Preface

1.1.1 Power Grid Emergency

In recent years, various natural disasters have been occurring frequently and showing an increasing trend. Disasters such as typhoons, heavy rainfall, geological earthquakes, snow and ice storms, and others have caused significant losses to the power grid, severely impacting the safe and stable operation of the grid and the normal production and operation of companies.

• (1) Typhoon disasters occur frequently. Since 1949, typhoons in Zhejiang and Fujian provinces have accounted for over 78% of all typhoons affecting State Grid Corporation's provinces and cities. These two provinces are hit by typhoons approximately four times each year. During the occurrence of typhoon meteorological disasters, a large number of power transmission equipment often shuts down, and even chain failures can lead to widespread power outages. For example, in 2004, Typhoon “Aere” made landfall in Zhejiang, damaging 3,342 km of transmission lines, causing 10 trips of 550 kV lines, power outage in 9 220 kV substations, 68 trips of 110 kV system lines, and 5 trips of main transformers. In 2016, Typhoon “Meranti” and Typhoon “Nepartak” caused 11 trips of 500 kV lines, 51 trips of 220 kV lines, and 109 trips of 110 kV lines in the Fujian power grid. Typhoon “Meranti” was particularly historic, causing damage to 7 500 kV towers and 15 220 kV towers. In 2019, the super typhoon “Lekima” made landfall in Zhejiang, resulting in 4,823 disrupted lines and power outages for 7.72 million households, causing massive losses.

• (2) Heavy rainfall severely affects power supply. From the 17th to the 21st of July 2021, Henan Province was hit by an unprecedented heavy rainfall. In many areas, the rainfall within 4 days exceeded the local annual average rainfall. The situation regarding rainfall, water levels, flood control, and disasters was extremely severe. The power infrastructure suffered significant damage. The cumulative impact of the disaster resulted in the shutdown of 42 35 kV and above substations in Henan's power grid. Among them, the entire Songshan 500 kV substation was completely shut down, leading to a rare and major N-7 risk in the main grid structure, severely compromising the reliability and power supply capacity of the power grid. A total of 1,854 10 kV and above power lines were disrupted, and 17 cities including Zhengzhou, Xinxiang, Anyang, Jiaozuo, Hebi, Kaifeng, Luoyang, and Zhumadian experienced power outages for 580,000 distribution transformers and 3.7433 million households. In the summer of 2020, the Jiangnan, middle and lower reaches of the Yangtze River, and Jianghuai regions experienced the longest rainy season in the past 20 years, as well as the highest rainfall recorded for the same period since 1961, resulting in severe flooding and geological disasters. 20 units in Anhui, Hubei, Hunan, Henan, Jiangxi, Sichuan, Chongqing, and Gansu suffered damage. The cumulative impact caused 26 substations of 35 kV and above to shut down, 4,833 power lines of 10 kV and above to be disrupted, and power outages for 149,000 distribution transformers and 9.2558 million users.

• (3) Earthquake disasters have severe consequences. On April 20, 2013, the strong 7.0-magnitude earthquake in Lushan, Ya'an, Sichuan Province, resulted in power outages for a total of 186,600 households in Ya'an, Chengdu, Neijiang, and Garze, with a loss of 446,700 kilowatts in load. Specifically, in the Ya'an region, 126,000 households experienced power outages, with a loss of 310,000 kilowatts (37.35% of the pre-earthquake load). Power outages were observed in the entire counties of Lushan, Baoxing, and Tianquan. In terms of damage to power grid equipment and facilities, a total of 34 substations of 35 kV and above were shut down, including 2 substations at 220 kV (Huanggang in Ya'an and Tianquan), 10 substations at 110 kV, and 22 substations at 35 kV. Two 500 kV substations experienced damage to a total of 3 main transformers and were shut down. In total, 626 units (including sets) of substation equipment were damaged, 265 power transmission and distribution lines of 10 kV and above were disrupted, including 1 line at 500 kV, 15 lines at 220 kV, 16 lines at 110 kV, and 61 lines at 35 kV. Additionally, 102 towers collapsed, 1,212 towers were damaged, and 83 lines were severed. In terms of the impact on power plants, the Sichuan power grid canceled the connection of 5 220 kV interconnecting power plants and 1 110 kV power plant. A total of 16 direct-controlled power generation units tripped (including 3 thermal power units and 13 hydropower units), of which 5 units had a capacity of over 100 MW. The total loss of output from the direct-controlled power generation units amounted to 1,917 MW. Seventeen power stations with a capacity of 68.83 MW managed by Ya'an Power Group were shut down. Two company personnel died (one was a construction worker from Hubei Transmission and Distribution Company in Sichuan, and the other was a worker from Ya'an Baoxing County Power Supply Company), and 13 personnel were injured, including 2 serious injuries.

• (4) Severe losses due to freezing rain and snow disaster. From 2008 to early 2018, China experienced more than 20 instances of rain, snow, and ice weather events in various regions, which had a significant impact on power grid safety. In total, 25,045 power transmission lines of 10 kV and above were disrupted, resulting in power outages for 44.0312 million users. The following are the most significant impacts:In early 2008, a rare large-scale and prolonged low-temperature rain, snow, and ice weather event occurred in southern China, causing disruptions to 119 lines at 500 kV, 348 lines at 220 kV, 888 lines at 110 kV, 35,385 lines at 10–35 kV, 8,381 towers for 110–500 kV lines, 300,000 towers for 10–35 kV lines, and 700,000 poles for lines below 10 kV. Additionally, 2,018 substations at 10–500 kV were damaged. The disaster affected power customers in 13 provinces, 95 regions, and 568 counties within the operating areas of State Grid and Southern Grid. From winter 2009 to spring 2010, there were seven instances of widespread strong winds, rain, snow, and ice weather events, leading to line galloping in 13 regions including Northeast China, North China, East China, and Central China. From winter 2015 to spring 2016, parts of Liaoning and North China experienced rain, snow, and ice weather events, resulting in 173 lines being disrupted and 98,400 households experiencing power outages. From winter 2017 to spring 2018, ice disasters affected 18 regions including East China, Central China, Northeast China, Southwest China, and Northwest China. Among them, Hunan, Hubei, Anhui, and Jiangxi were the most severely affected, causing 6,729 line disruptions and power outages for 10.6836 million households.

1.1.2 Emergency Requirements for the Power Grid

• (1) The government has placed high demands on emergency response in the power grid sector

Since the 19th National Congress of the Communist Party of China, the Party Central Committee has put forward the requirement to strengthen, optimize, and coordinate the national emergency response capacity, and build a unified, authoritative, and efficient national emergency response system with unified command and clear responsibilities. The goal is to enhance capabilities in ensuring production safety, maintaining public safety, disaster prevention, reduction, and relief, in order to ensure the safety of people's lives and property as well as social stability. In the context of national emergency response capacity building, monitoring and early warning of risks and hazards, as well as disaster loss assessment, have become of paramount importance.

All regions and relevant departments are focusing on curbing major production safety accidents and promoting the upgrading of intelligent monitoring systems for major risks in high-risk industries. They are implementing high-level planning and step-by-step efforts to improve the coverage and quality of major risk intelligent monitoring systems. They are also establishing advanced Internet of Things monitoring systems with a scientific layout of various sensing devices to effectively control the risks of major production safety accidents. Accelerated work is being carried out in the monitoring and early warning of safety production risks, including accessing key safety production online monitoring data from high-risk industry enterprises, conducting remote online inspections and enforcement, and supervising the effective implementation of safety production responsibilities by enterprises.

A comprehensive approach is being employed, using various means such as on-site inspections, sensor monitoring, video surveillance, and remote sensing monitoring, to carry out dynamic monitoring of natural disaster hazards. Efforts are being made to improve the timeliness and quality of natural disaster monitoring and early warning. Moreover, regions and relevant departments are continuously strengthening research on emergency command and decision-making support. National departments are gradually realizing the scientific resource allocation and deployment for disaster response based on the national emergency management big data application platform. They are improving the emergency command and dispatch system, conducting comprehensive analysis and dynamic display of disaster situation, evacuation and resettlement of affected populations, and establishing an emergency rescue command network connecting emergency management departments at all levels, emergency rescue teams, and disaster sites. This enables unified command, multi-party coordination, and collaborative response, effectively ensuring scientific and efficient emergency command decisions.

The joint release of a document by the State Council's Work Safety Committee, the National Disaster Reduction Committee Office, and the Ministry of Emergency Management (Document No. [2019] 8) clearly requires the strengthening of emergency basic information management, integration of resources, promotion of information sharing and utilization, reinforcement of supervision over disaster risks and hazards, enhancement of safety production and comprehensive disaster prevention, reduction and relief capabilities, and the formation of a distinctive Chinese emergency management system characterized by unified command, versatility, responsiveness, coordination between different levels, and integration of peacetime and wartime efforts. The goal is to effectively guarantee the safety of people's lives and property and social stability.

Strengthening the monitoring and early warning of risks and hazards is crucial. All regions and relevant departments should focus on curbing major production safety accidents and implement high-level planning to promote the improvement of intelligent monitoring systems for major risks in high-risk industries such as coal mining, non-coal mining, hazardous chemicals, fireworks, transportation, metal smelting, and fishery production. The aim is to increase the coverage density and construction quality of these monitoring systems. It is necessary to establish and improve advanced Internet of Things monitoring systems with a scientifically designed layout of various sensing devices to effectively control the risks of major production safety accidents.Efforts should be accelerated in conducting monitoring and early warning of safety production risks. This includes accessing key safety production online monitoring and surveillance data from high-risk industry enterprises, enabling remote online inspections and enforcement, and supervising the effective implementation of safety production responsibilities by enterprises. A comprehensive approach should be adopted, utilizing various methods such as on-site inspections, sensor monitoring, video surveillance, and remote sensing monitoring to carry out dynamic monitoring of natural disaster hazards. The goal is to enhance the timeliness and quality of natural disaster monitoring and early warning.

Enhancing the level of intelligent emergency prediction and early warning is essential. The Ministry of Emergency Management guides all regions and relevant departments to utilize advanced technologies such as big data to analyze changes in information regarding major risks and significant hazards. This includes identifying potential sources of danger, strengthening prediction and judgment, and improving data-supported intelligent emergency prediction and early warning capabilities. Furthermore, leveraging the foundation of emergency basic information, in-depth research on catastrophic and compound disasters should be conducted. This involves refining trend analysis of disaster incidents and developing emergency prediction models. By assessing the occurrence and development patterns of disasters, proactive measures and recommendations can be provided for emergency management. The goal is to prevent and minimize casualties and property losses caused by disasters to the greatest extent possible.

Enhancing the support for emergency command decision-making is crucial. All regions and relevant departments should rely on the National Emergency Management Big Data Application Platform to achieve scientific resource allocation and deployment for disaster response. It is important to improve the emergency command and dispatch system, conduct comprehensive analysis and dynamic display of disaster situations, evacuation of affected populations, and resettlement information. Establishing an emergency rescue command network that connects emergency management departments at all levels, emergency response teams, and disaster sites is essential.This network enables unified command, multi-party coordination, and collaborative response, effectively ensuring the scientific and efficient decision-making of emergency command.

• (2) The company's disaster and emergency command technology urgently needs improvement

Since 2008, State Grid Corporation of China has embarked on the construction of its emergency command information system. The system has played a proactive role in the company's emergency response to unforeseen events in recent years. However, it lacks sufficient capabilities in on-site information collection, information exchange, information integration, situational analysis, and other aspects of emergency command and decision-making. Specifically, the following issues have been observed.

Inefficient collection of post-disaster damage information: The conventional method of collecting damage information heavily relies on manual on-site surveys and subsequent reporting. This approach leads to challenges such as difficulties in obtaining data, slow data acquisition, significant limitations, and a limited number of data sources. These issues hinder scientific decision-making during emergency response and impede the timely and comprehensive collection of data on damaged equipment at the disaster site. The efficiency of data collection needs improvement.

Insufficient flexibility in emergency information exchange: After natural disasters such as typhoons, heavy rainfall, geological earthquakes, snow and ice storms, communication between on-site rescue personnel and on-site rescue command centers or emergency command centers mainly relies on telephone or text messaging, lacking flexibility. This limits the ability to upload and transmit on-site images, audiovisual disaster information, and hampers effective communication.

Limited level of intelligence in emergency support decision-making: Due to the lack of real-time data collection and analysis of various professional emergency data, emergency command mainly relies on the experience of command personnel and relevant provisions of emergency plans. The support provided by data analysis results for emergency decision-making needs improvement.

Lack of intelligent perception of power grid disaster situations and emergency command platforms: The current emergency command information system primarily focuses on daily emergency management tasks and fails to provide intelligent perception of power grid disaster situations. This deficiency undermines emergency command support and does not meet the requirements of the company's ubiquitous power Internet of Things construction.

1.1.3 Emergency Objectives for the Power Grid

To cope with emergency incidents in the power grid, it is necessary to fully utilize Internet of Things (IoT) technology and overcome key technologies such as diverse data collection, information integration, real-time interaction, and situational prediction. The development of an intelligent sensing and emergency command system for power grid disasters and innovation of the power grid disaster command system are required. This will enable rapid and automated collection of on-site information during power grid emergencies and real-time integration with power emergency command centers at all levels. By integrating information analysis and power grid damage prediction, the efficiency and accuracy of emergency decision-making can be improved, thereby enhancing emergency response efficiency. It supports comprehensive operations such as joint emergency command and optimized coordination analysis, thereby enhancing emergency command capabilities and the level of power grid security:

• (1) Improve the efficiency of power emergency response by enabling rapid disaster perception, accurate analysis and trend prediction of disasters, and efficient collaborative interaction, thus reducing power outage duration and minimizing economic losses for the company.

• (2) Establish an intelligent sensing and emergency command platform for power grid disasters, and achieve commercialization through industrial conversion, resulting in economic benefits.

• (3) Shorten the restoration time through the operation and use of the power grid disaster sensing and emergency command system, enhance the social responsibility of power grid enterprises, and generate social benefits.

1.2 Current Development Status

1.2.1 Current State of Grid Sensing

The United States has been at the forefront of research on grid sensing technology. The U.S. Department of Energy and several research institutions started investigating situational awareness technology in power systems several years ago and have achieved significant results. With the advancement of the Federal Smart Grid Deployment Plan, power companies in New York State have begun implementing situational awareness technology in their power systems to enhance operational management, improve visibility and reliability of the grid, and enhance equipment utilization efficiency.

The Smart Grid Standards Research Group of the Electric Power Research Institute (EPRI) believes that a smart grid should possess six main functionalities, including wide-area situational awareness, demand response, energy storage, power transmission, advanced metering, and distribution grid management. Among these functionalities, situational awareness plays a crucial role in power systems. It helps understand the state of power system components, identify hidden problems in a timely manner, coordinate the control of numerous power system components, and provide effective management systems and optimal solutions for problem resolution.

EPRI has listed several typical applications of situational awareness in power systems, including accident analysis. Accident analysis is an application of Energy Management Systems (EMS) used to analyze the security of the power system, such as its ability to withstand the shutdown of critical infrastructure within the power system. Situational awareness systems can compute, identify, and define priorities, and they can predict the likelihood and magnitude of problems such as equipment overcurrents, excessive bus voltages, and system instability when unexpected accidents occur in the future, such as equipment failures or outages.

Indeed, the application research of situational awareness technology in the domestic power grid started relatively late. Due to the significant social and economic impacts caused by multiple power outages both domestically and internationally, the security of the power grid has become more prominent. As a result, situational awareness technology has gradually become a focal point in power grid research in recent years.

In 2004, the State Grid Electric Power Research Institute (SGEPRI) initiated the research on the fundamental theory and key technologies of the wide-area security defense system in power systems. This was the first major project funded by the National Natural Science Foundation of China in the field of power systems. The project aimed to gain a deep understanding of the dynamic behavior and characteristics of large-scale power systems, explore corresponding analysis methods, develop theories and methods for protection and control based on wide-area dynamic phasor measurement, and establish theories for online dynamic early warning of power system security and stability. From this research, it can be seen that the capability requirements for situational awareness were initially established.

In recent years, research on situational awareness technology in the domestic power grid has mainly focused on grid dispatching. The information and data in the power grid are vast and complex. The challenge lies in presenting operational information in a vivid manner, providing real-time data categorized for dispatchers, and mining data that has significant impacts on grid operations. This enables early warning and control of system weak links and potential security issues, which is an important issue faced by grid dispatchers.

The Key Laboratory of Smart Grid in Sichuan Province has proposed a five-indicator system covering various aspects of the power grid. These indicator systems can quantitatively describe the characteristics of different parts of the power grid, enabling effective analysis, evaluation, and prediction of the macroscopic security situation of the power grid.

In 2013, SGEPRI led the research project “Research on Power Grid Operation Trajectory Characterization Method Based on Situational Awareness,” which aimed to accurately and effectively predict the security situation of the power grid by understanding and comprehending various factors influencing the changes in grid operation. The project also aimed to construct an indicator system to characterize the operation trajectory of the power grid through the extraction and summarization of massive operational information. The research contents of the project included comprehensive state awareness technology for grid operation considering external environmental influences, real-time operation trajectory indicator systems, and power grid operation trajectory characterization methods based on risk degree. The goal was to lay the foundation for achieving automatic intelligent dispatch control through online calculation and control of operational trajectory indicators and to assess future operational situations based on the indicator system of risk degree.

1.2.2 Current Status of Power Grid Emergency Command

• (1) Power Grid Emergency Organization System

In January 2005, the former National Electricity Regulatory Commission established the Emergency Leadership Group for Large-scale Power Grid Blackout Incidents. Its purpose was to unify and coordinate the emergency response efforts for large-scale power grid blackout incidents nationwide. At the same time, State Grid Corporation of China, China Southern Power Grid, and major power generation companies established their respective emergency management organizational systems as required to ensure the orderly organization and implementation of emergency management tasks. This initiative strengthened the construction of emergency repair and rescue teams and enhanced the ability to respond quickly to unexpected events.

• (2) Power Grid Emergency Response Plan System

China's Power Grid Emergency Response Plan System has been continuously improved since the implementation of the “National Emergency Response Plan for Dealing with Large-scale Power Grid Blackout Incidents” in 2005. Power companies have developed emergency response plans for different levels and types of accidents, focusing on rescue, handling, and power grid restoration based on their specific circumstances.

Currently, China Southern Power Grid, State Grid Corporation of China's North China, Northeast China, East China, Central China, and Northwest China subsidiaries, as well as the power grid (electricity) companies of 31 provinces (autonomous regions, municipalities directly under the central government), have formulated emergency response plans to deal with major and extraordinary incidents in the power grid, accompanied by specialized contingency plans. In addition, over 310 power supply (electricity) companies and their grassroots units across the country have also developed corresponding emergency plans. Major power generation enterprises have also established overall emergency response plans and specialized plans for specific situations, such as “Black Start Plan,” “Factory Power Supply Plan,” “Hydropower Dam Accident Emergency Plan,” and “Flood Control Emergency Plan.“ These emergency plans have played a vital role in practice.

For example, on July 1, 2006, a situation occurred in Henan Province where four 500 kV and five 220 kV transmission lines tripped, causing multiple power generating units to shut down and resulting in power oscillation incidents in the Central China Power Grid, posing a threat to the safety and stable supply of the power grid. In this case, the emergency response plan played a critical role. State Grid Corporation of China promptly initiated the emergency response mechanism, effectively preventing the accident from escalating and successfully avoiding a large-scale power grid blackout incident.

• (3) Power Grid Emergency Information Platform

Each power company has established its own information reporting system and has intensified the construction of emergency management information platforms. State Grid Corporation of China and China Southern Power Grid rely on their existing dispatch communication systems to integrate network communication resources and establish robust information communication platforms. Currently, regulatory authorities are also promoting the construction of power grid emergency command information platforms. This involves leveraging existing specialized information systems and command systems in the power grid, expanding their functionalities, integrating, transmitting, and sharing emergency information resources, uploading and issuing command instructions, and achieving interoperability with government emergency platforms.

• (4) Emergency Training and Plan Drills

Many power companies actively carry out emergency training, plan drills, and joint accident exercises to enhance their emergency response capabilities in dealing with power grid-wide blackouts and other power emergencies. These activities aim to improve the comprehensive handling capabilities of major power emergencies and the overall coordination of social emergency response during large-scale power outages. For example, on June 8, 2006, the State Grid Dispatch Center successfully organized the 2006 Peak Summer Joint Anti-Accident Exercise, involving five regional power grids of the State Grid Corporation. A total of 382 units participated in the exercise, with over 8,000 participants. The collaborative coordination abilities of personnel at all levels in handling accidents were comprehensively exercised. In October 2006, China Southern Power Grid Company successfully held a joint emergency drill for a large-scale power outage in Guangdong Province, with the participation of 34 units, achieving the desired results.

1.3 Organization of the Book

Chapter 2 of this book introduces the fundamental knowledge of grid perception and emergency command. The subsequent chapters are organized based on the approach of key technology research, system prototype development, and application validation, as illustrated in Fig. 1.1. Firstly, it covers the intelligent collection of diverse information on grid damage. Secondly, it discusses the fusion analysis and prediction of grid damage information. Thirdly, it explores real-time information exchange technology between the emergency site and the command center. Fourthly, it delves into grid emergency decision-making technology. Lastly, it presents the development of a prototype for power emergency site security control and its application validation in power grid companies.

Fig. 1.1

Overall research content of the project

Chapter 3: Multi-source Information Collection Technology for Power Grid Disaster Damage Assessment.

The main content includes the rapid acquisition and automated collection techniques of diverse information on typical power equipment damages based on the Internet of Things (IoT). A method and technical scheme for collecting diverse information on power equipment damages based on the power IoT are proposed. A technical scheme for reconnaissance and identification of power line disasters using unmanned aerial vehicles (UAVs) is presented to achieve automatic statistical analysis of power equipment losses. Intelligent collection, sharing, and integration techniques for regionally relevant social public emergency information related to damages are introduced to support the integration and fusion of damage information and achieve integration with government emergency management big data platforms, thereby enhancing the multi-dimensional data collection capability of the power grid disaster.

Chapter 4: Integration and Comprehensive Prediction Technology of Power Grid Damage Information.

The main content includes the construction technology of typical disaster event loss models, introduction of typical power grid disaster event loss models, proposing information integration and fusion methods and technical schemes for power grid damage information collection - damage model library - emergency command comprehensive database, supporting intelligent perception of power grid disasters. Information fusion technology between the emergency command comprehensive database and the damage model library, as well as fuzzy dynamic power grid loss prediction technology, are discussed. Mastering analytical techniques such as dynamic power grid loss prediction based on multiple data sources enhances the scientificity of emergency command.

Chapter 5: Real-time Interactive Technology for Power Grid Emergency Field Operations.

The main content includes real-time interactive technology for mobile-friendly neighbor-to-neighbor communication in power emergency field operations. It investigates real-time information exchange technology between the scene of unexpected events and the emergency command center cluster. It proposes neighbor-to-neighbor communication technology and long-distance cluster information real-time interaction technology between the field and the command center. Efficient methods for submitting various types of information are developed to enhance information exchange capabilities among different departments and locations involved in emergency response.

Chapter 6: Power Grid Emergency Decision-Making Technology.

The main content includes the situational mapping and three-dimensional visualization command technology for power grid disasters and unexpected events. It investigates comprehensive social source information emergency command decision-making technology in situations where information is lacking at the emergency scene.

Chapter 7: Power Grid Disaster Intelligent Perception and Emergency Command System.

The main content includes the overall architecture and technical scheme of the power grid disaster intelligent perception and emergency command system. It proposes situational analysis models for power grid disaster and unexpected events, as well as information interaction models between the command center and the field. The chapter introduces the power grid disaster intelligent perception and emergency command system and its pilot application in power grid enterprises. It aims to achieve intelligent perception of power grid disasters and assist decision-making and visualization command in situations where information is missing at the emergency scene. This system effectively improves emergency command efficiency in disaster assessment, operation command, and resource allocation.